Abstract
Power plants based on organic Rankine cycle (ORC) are known for their capacity in converting low and medium-temperature energy sources to electricity. To find the optimal operating conditions, a designer must evaluate the ORC from different perspectives including thermodynamic performance, technological limits, economic viability, and environmental impact. A popular approach to include different criteria simultaneously is to formulate a bi-objective optimization problem. This type of multi-objective optimization (MOO) allows for finding a set of optimal design points by defining two different objectives. Once the optimization is completed, the decision-making analysis shall be carried out to identify the final design solution. This study aims to develop a decision-making tool for facilitating the choice of the optimal design point. The proposed procedure is coded in MATLAB based on the commonly used Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). By providing the capability to graphically identify the decisions taken, the tool developed in the study is called Tracking and Recognizing Alternative Design Solutions (TRADeS). Analysis of our data shows that certain regions of Pareto set points should be excluded from the design space. It was noted that in these regions a high rate at which one of the objectives moves away from its ideal value coincides with a low rate at which the second criterion approaches its ideal solution. Hence, it was recommended that the criteria weights corresponding to excluded regions of the Pareto set should be discarded when selecting the final design point. By comparing the results obtained using the proposed model to those of existing decision-making techniques, it was concluded that while the known approaches are appropriate for an easy and fast selection of the final design point, the presented procedure allows for a more comprehensive and well-rounded design. It was shown that our design tool can be successfully applied in the decision-making analysis for problems that aim at optimizing the ORC using two design criteria. Finally, the proposed software benefits from a generic structure and is easy to implement which will facilitate its use in other industrial applications.
Highlights
The depletion of fossil fuels combined with increasing electricity demand is the main reason for the efforts aiming at the utilization of alternative energy sources
For a better understanding of the developed tool, an illustrative decision-making procedure applied for the results of bi-objective optimization is presented
The exergy efficiency ηex and total heat transfer area Atot were defined as the criteria optimizing the operation of the organic Rankine cycle (ORC) power plant
Summary
The depletion of fossil fuels combined with increasing electricity demand is the main reason for the efforts aiming at the utilization of alternative energy sources. As a technology capable of converting renewable and waste heat to electricity, the organic Rankine cycle (ORC) power plant has been widely investigated in the last decade. The growing interest in developing ORC systems is partly because it lends itself well to applications including geothermal energy [1], solar thermal energy [2], biomass energy [3], and low-grade waste heat recovery [4]. Energies 2020, 13, 5280 successfully adapted to a low [5] and medium [6] temperature energy sources due to great variety of possible working fluids, including refrigerants [7], hydrocarbons [8] or siloxanes [9]. One way to include various aspects simultaneously is to formulate a bi-objective optimization problem
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